Information flow clustering via similarity of a propagation tree

N Terunuma, Y Yaguchi, Y Watanobe… - 2014 Joint 7th …, 2014 - ieeexplore.ieee.org
N Terunuma, Y Yaguchi, Y Watanobe, R Oka
2014 Joint 7th International Conference on Soft Computing and …, 2014ieeexplore.ieee.org
Social network services (SNSs) serve numerous users with large amounts of information of
different kinds. On an SNS, information will propagate on a user network, which is
represented as a complex network in general but can be reformed as a tree by using the
direction of propagation and allowing duplication. Our goal in this study was to show the
propagation of a particular kind of information on an SNS, as well as the clustering of a
similar propagation scheme for each user. For this goal, we used elastic tree pattern …
Social network services (SNSs) serve numerous users with large amounts of information of different kinds. On an SNS, information will propagate on a user network, which is represented as a complex network in general but can be reformed as a tree by using the direction of propagation and allowing duplication. Our goal in this study was to show the propagation of a particular kind of information on an SNS, as well as the clustering of a similar propagation scheme for each user. For this goal, we used elastic tree pattern matching to calculate the similarity of two tree structures. A set of users are propagated from source to destination in the same or similar way, and these users are given information from a similar source. We also aimed to find the high-influence person who is at the start of the same or similar propagation, which will indicate that she/he is the moderator of a topic. We used tumblr data for the experiment. Findings indicated that the similar part of each information propagation tree on tumblr was too small for the clustering propagation pattern.
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